"Do You Know What You Don't Know?" Exploring Monitoring Accuracy Across Domains of General Knowledge, Financial Calculation, and Probability Calculation
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Confidence and its accuracy have been most commonly examined in domains such as general knowledge and learning, with less study of other domains, such as applied knowledge and problem-solving. Monitoring accuracy in real-world competencies may depend on characteristics of the domain. The current study examined whether monitoring accuracy, both calibration (resistance to overconfidence) and resolution (discrimination) indices, are stable within individuals and across tasks that represent highly diverse areas. The well-established domain of general knowledge and two understudied applied domains of financial calculation and probability calculation were examined. In addition, correlations between monitoring accuracy and cognitive abilities (intellectual ability and working memory) and several aggregated judgments regarding each task as a whole (ratings of predicted and postdictive performance, task difficulty, and effort required), as well self-perceptions relating to test anxiety and academic self-concept were explored. Calibration was significantly positively correlated across tasks, reflecting a person-centered trait, but not resolution. Cognitive abilities were predictive of both calibration and resolution across tasks, while other task-specific judgments and self-perception variables demonstrated varied and tasks specific associations. Monitoring accuracy was not predictive of real-world outcomes including academic average and learning challenges. Overall study findings support that when considering a wide range of domains, calibration displays domain-generality, while resolution displays domain-specificity.